Today, mobile devices are configured to include various types of built-in sensors along with powerful processing units and easy internet connectivity that make the mobile devices a perfect tool in today's pervasive sensing and/or computing era. Examples of such mobile devices includes palmtop, personal digital assistant (PDA), cell phone, pocket pc, laptop, smartphone, tablet computer, smartwatch, pager and the like.
The configuration of the mobile devices leads to development of Internet of Things (IoT) enabled intelligent applications across diverse domains. As a result, various complex algorithms are being ported to the mobile devices on regular basis as free or commercial applications. For example, mobile devices can be utilized for estimating a range of parameters for monitoring tasks including motion, location, heart rate and the like. For such monitoring, the sensors embodied in the mobile devices are utilized extensively for collecting various modalities of data (such as, time-series, image, video, pressure, and so on).
The complex applications perform complex processing operations at the mobile devices to enable monitoring by the sensors. However, to perform complex processing operations, the processing and memory capabilities of the mobile devices should match with the complex processing operations. Currently, there is a mismatch between the processing and memory capabilities of the mobile devices and those needed for performing complex processing operations, and hence it takes long processing time for such operations. A mobile sensing framework may be developed that may ease development of mobile device based application, so as to cater for end-to-end mobile sensing solutions and simplify the processing operations performed therefor.